Accurate and robust foreground image segmentation is a computationally expensive process requiring significant resources to perform in real time. Although there are various segmentation techniques that are far less computationally expensive, such as simple thresholding using depth images, a significant shortcoming of those techniques is inaccurate segmentation that conventionally has been difficult to correct with automated techniques. For example, many such segmentation techniques fail to label pixels at or near edges of foreground portions of images.